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Brainomaly

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software/brainomaly

[WACV 2024] Official PyTorch implementation of Brainomaly

Machine-generated from the listed sources and not yet reviewed by a human.

Brainomaly project image
GitHub preview card for mahfuzmohammad/Brainomaly. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
MIT(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
abnormality-detection · alzheimers-disease · anomly-detection · disease-detection · generative-adversarial-network · headache-diagnosis · medical-imaging · mri · ood-detection
Regulatory
unknown
similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • MRI_Style_Transfer_using_CycleGANgenerative-adversarial-network · medical-imaging · mri

    Build a Generative adversarial model (modified U-Net) which can generate artificial MRI images of different contrast levels from existing MRI scans.

  • ADMIRE-DLalzheimers-disease · mri

    A suite of tools for the preprocessing of MRI images and the training of CNNs for the classification of Alzheimer's Disease patients.

  • Alzheimer_ensemble_transfer_learningalzheimers-disease · mri

    Alzheimer prediction using Ensemble Transfer Learning

  • master_codealzheimers-disease · mri

    Various code from my master's project

  • A Combined ResNet-DenseNet Architecture with ResU Blocks (ResU-Dense) for 12-lead ECG Abnormality Classification

  • ResUNet-LCabnormality-detection

    2D residual U-Net (ResUNet) and a lead combiner (LC) for 12-lead ECG Abnormality Classification

sources
  1. api.github.com/repos/mahfuzmohammad/Brainomaly
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2024-02-13, 13 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/13.json→ .entries["brainomaly"]

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